Researchers from the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) have developed a new imaging technique which makes it possible for scientists to see high-res views of lightweight atoms using a new method known as midi-stem.
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Researchers already know that electrons can help view tiny objects up to their atomic scale, and they deploy the scanning transmission electron microscopy (STEM) method of using electron microscopy to view strong and resistant material, but the only danger is that STEM can damage fragile samples.
So they came up with the matched illumination and detector interferometry STEM (MIDI-STEM) which uses an optical device known as phase plate which changes alternating peak-to-trough properties of the electron beam. With MIDI-STEM, materials not visible to STEM become visible here.
The study was published in the journal Nature Communications from the University of Oregon, Gatan Inc. and Ulm University in Germany as well as Lawrence Berkeley National Laboratory.
“The MIDI-STEM method provides hope for seeing structures with a mixture of heavy and light elements, even when they are bunched closely together,” said Colin Ophus, a project scientist at Berkeley Lab’s Molecular Foundry and lead author of a study.
Co-author of the study and a Berkeley Lab scientist at the Molecular Foundry, Peter Ercius, noted that STEM is great for tough and resilient materials that can withstand intense electron beams, and cryo-EM good for imaging biological samples, both can be done at the same time using MIDI-STEM technique.
To perfect the results of the research, the scientists combined phase plate technology with the highest resolution STEM at Berkeley Lab’s Molecular Foundry, and a high-speed electron detector.
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“If you can lower the electron dose you can tilt beam-sensitive samples into many orientations and reconstruct the sample in 3-D, like a medical CT scan. There are also data issues that need to be addressed,” Ercius revealed against the fact that faster detectors generate huge amounts of data.